Digital still cameras (or DSCs) are currently among the devices most commonly employed for acquiring digital images. The fact that both sensors of ever greater resolution and low-cost and low-consumption digital signal processors (DSPs) are readily available in commerce has led to the development of digital still cameras capable of acquiring images of very considerable resolution and quality.
In these cameras, as also in traditional still cameras, a problem that is, as yet, difficult to solve is represented by estimating the best exposure to be used in the acquisition phase.
Exposure control, obtained by acting both on the size of the diaphragm aperture and the shutter timing, makes it possible to control the amount of light that strikes the sensor—and, more particularly, the photosensitive cells of which it is made up—during the acquisition. In digital still cameras there also exists the possibility of regulating the exposure by varying the gain or, analogously, the sensitivity of the photosensitive cells.
A correct exposure makes it possible to acquire images of a good and uniform tonality, to reproduce the contrast of the scene in an optimal manner and to render any lighting variations within the scene in the best possible way by exploiting the limited dynamic response of the acquisition instrument in an optimal manner. Indeed, given the finite number of bits available for the numerical representation of the pixels and also on account of the sensor characteristics, digital still cameras have a limited response to the luminance variations to be found in a given scene, that is to say, a limited dynamic range.
Modern digital still cameras utilize several techniques for automatically setting the exposure. These techniques are known as “exposure metering” and operate in conformity with a multitude of different criteria. All of them are, however, based on measurements that estimate the quantity of light associated with or incident on the scene that is to be acquired or on particular regions of that scene.
Some techniques are completely automatic, cases in point being represented by those based on “average/automatic exposure metering” or the more complex “matrix/intelligent exposure metering”. Others, again, accord the photographer a certain control over the selection of the exposure, thus, allowing space for personal taste or enabling him to satisfy particular needs.
Notwithstanding the great variety of the known methods for regulating the exposure and notwithstanding the complexity of some of these methods, it is not by any means rare for images to be acquired with a non-optimal or incorrect exposure.
In any case, there does not exist a precise definition of the best exposure, because this depends both on the contents of the image and the personal taste of the observer. Given a scene that does not call for a particular exposure setting, it is possible to abstract a generalization and to define, as best, the particular exposure that enables one to reproduce the most important regions (deemed to be such in accordance with contextual or perceptive criteria) with a level of grey, or brightness, more or less in the middle of the possible range.
Optimal exposure therefore reproduces a digital image that, when represented in YCrCb format, is characterized in that the mean of the digital values of the luminance plane Y relating to the most important regions has a value approximately at the center of the range of the possible digital values.
Various so-called correction methods are known to obtain an improvement of the quality of the acquired image, generally by modifying the luminosity distribution within the image.
One of the most common of these is the so-called “histogram equalization”, a method that has several known variants.
Histogram equalization, described in detail—among others—in U.S. Pat. No. 5,923,383, extracts from an image the histogram of the distribution of the digital values corresponding to the light intensity of the pixels and then, equalizing this histogram, produces an image of better quality.
A problem associated with this method—in common with other known exposure correction methods—is that it takes no account of the fact that in the image there exist regions that are more important from either a perceptive or a contentual point of view.
Furthermore, the methods known in the state of the art perform the correction by acting on the image after the interpolation process traditionally employed in digital still cameras for producing an image on three full-resolution planes starting from the single-plane colored CFA (Color Filter Array) image produced by the sensor. For this reason, the known correction methods are not optimized from the point of view of computation cost.